Digital Twin Benefits and Challenges in Asset Management During The O&M Phase: A Systematic Review

Abstract

Asset management during the operations and maintenance (O&M) phase of construction projects is a complex activity that encompasses various functions including asset planning, asset maintenance, and resource allocation. This activity stands at a crossroads: its significance in ensuring the seamless operation of facilities is unquestionable, yet this success hinges on the effective harnessing of the sheer volume of data. Recently, Digital Twin (DT) has emerged as a transformative solution for the construction industry creating digital replicas of physical entities bi-directionally transferring data in a specific frequency and fidelity. While there are several studies exploring the implementation of DT in the O&M phase of construction projects presenting a wide variety of benefits and challenges based on their specific viewpoint, a comprehensive analysis covering all perspectives is still missing. As a response, this study systematically reviews the available literature on this topic from 2018 to 2024 extracted from two databases, Google Scholar and Science Direct. The benefits and challenges are identified, categorized, and prioritized based on their frequency through the literature aiming to help facility managers. Predictive maintenance, real-time monitoring/data, improved/Enhanced decision-making, and optimization of operations/maintenance are identified as the top four benefits, while the four most critical challenges are data integration issues, integration with existing systems, high implementation costs, and technical complexity. The findings showcase the potential of DT for managing assets and present academicians and practitioners with a prioritized list of benefits and challenges to be further investigated and realized. Furthermore, it is vital to consider that successful DT implementation for asset management during the O&M phase is intricately linked to the data collected across earlier project phases which highlights complementary future works to be focused on developing comprehensive processes for mapping the data infrastructure for gathering asset data throughout the project lifecycle.